Tracking fungal species-level responses in soil environments exposed to long-term warming and associated drying

Abstract Climate change is affecting fungal communities and their function in terrestrial ecosystems. Despite making progress in the understanding of how the fungal community responds to global change drivers in natural ecosystems, little is known on how fungi respond at the species level. Understanding how fungal species respond to global change drivers, such as warming, is critical, as it could reveal adaptation pathways to help us to better understand ecosystem functioning in response to global change. Here, we present a model study to track species-level responses of fungi to warming—and associated drying—in a decade-long global change field experiment; we focused on two free-living saprotrophic fungi which were found in high abundance in our site, Mortierella and Penicillium. Using microbiological isolation techniques, combined with whole genome sequencing of fungal isolates, and community level metatranscriptomics, we investigated transcription-level differences of functional categories and specific genes involved in catabolic processes, cell homeostasis, cell morphogenesis, DNA regulation and organization, and protein biosynthesis. We found that transcription-level responses were mostly species-specific but that under warming, both fungi consistently invested in the transcription of critical genes involved in catabolic processes, cell morphogenesis, and protein biosynthesis, likely allowing them to withstand a decade of chronic stress. Overall, our work supports the idea that fungi that invest in maintaining their catabolic rates and processes while growing and protecting their cells may survive under global climate change.


Introduction
Climate change is affecting soil micr obial comm unities , and thus , the cycling of carbon (Melillo et al. 2002, Allison and Treseder 2011, Cavicchioli et al. 2019, IPCC 2021 ).Because soil microbes mediate biogeochemical cycles, their responses to global change driv ers, suc h as warming and warming-induced drying (r eferr ed to as warmed and warming from here onw ar ds), have resulted in ecosystem-scale impacts to the carbon cycle, including changes in decomposition and CO 2 emissions (Allison andTreseder 2008 , Melillo et al. 2017 ;Romer o-Oliv ar es et al. 2017a ,b ).These impacts ar e partiall y caused by comm unity-le v el c hanges, wher e pathogenic and other weak-decomposer fungi (i.e.fungi with a limited suite of enzymes to break down organic matter) increase in abundance under warming, inv esting mor e r esources in cell metabolic maintenance rather than in decay (e.g.Treseder et al. 2016, Solly et al. 2017, Morrison et al. 2019, Romer o-Oliv ar es et al. 2019 ).Ho w e v er, w e kno w very little about how fungi at the speciesle v el ar e r esponding and ada pting to global c hange driv ers.We know e v en less about what these r esponses and potential physiological and molecular adaptation pathways look like in natural soil microbial communities.
Fungal species-le v el r esponses to global c hange driv ers hav e been documented in laboratory settings.For example, Neurospora discreta was experimentally evolved for 1500 generations under ele v ated temper atur e conditions, r esulting in gr eater r esource investment in respiration and spore production at the expense of biomass production (Romero-Olivares et al. 2015 ).Other shorter time scale studies found similar results; catabolic processes, such as growth and respiration, are impacted by elevated temperature (Malcolm et al. 2008 , Crowther andBradford 2013 ).Acclimation studies in Neurospora crassa r e v ealed that when exposed to heat shoc k (i.e.temper atur e shift fr om 15 • C to 42 • C), N. crassa invested in the production of molecules for cell homeostasis, such as heat shoc k pr oteins, while arr esting the pr oduction of cell mor phogenesis pr oteins, suc h as actin and tubulin (Mohsenzadeh et al. 1998 ).Whether or how microbial species respond and/or adapt to warming in natural soil en vironments , remains largely unknown (DeAngelis et al. 2019 ).
Tr ac king species-le v el r esponses to warming in natur al environments can offer insight into potential adaptation pathwa ys .Her e, we tr ac ked species-le v el r esponses in a natur al soil envir onment by ma pping comm unity le v el soil metatr anscriptomes against the genome of two wild fungal species isolated from control conditions and warmed treatment soils in a long-term field warming experiment.We chose Mortierella spp.and Penicillium swiecic kii (r eferr ed to as Mortierella and P enicillium her einafter) for two main reasons.First, they wer e pr e viousl y found to be the most abundant and pr esumabl y activ e species-based on tr anscript counts-in contr ol conditions and warmed treatment soils alike (Romer o-Oliv ar es et al. 2019 ).Second, these fungi are free-living and easy to isolate and grow in culture compared to, for example, ectomycorrhizal fungi, whic h r equir e a host.This meant that we were able to consistently isolate them from soil samples from both control conditions and warmed treatment soils.Since the fungal community shifts in composition in response to global c hange driv ers (e.g.Tr eseder et al. 2016, Morrison et al. 2019 ), species that are highly abundant under control conditions may decrease in abundance or even disappear under treatment conditions, ther efor e, isolating the same fungal species from different soil samples is v ery c hallenging.Our objectiv e was to investigate how individual fungal species respond to global change drivers in a natural soil environment to advance our understanding on fungal responses to climate change and to gain insight on potential adaptation pathwa ys .Specifically, we in vestigated potential physiological changes at the species level in a natural soil environment exposed to global change drivers, which provides a more r ealistic ov ervie w of fungal r esponses to global climate c hange compared to studies done under controlled laboratory settings.We addressed our objective by asking the following questions, (i) What changes do Mortierella and Penicillium experience, at the transcription le v el, when exposed to warming in a natur al soil environment?(ii) What functional pathways and genes are affected in each species in response to warming? (iii) Are there any impacts to gene regulation in response to warming? and (iv) How are Mortierella and Penicillium strategizing resource investment under warming ?

Materials and methods
Our field warming experiment was located in a mature black spruce ( Picea mariana ) forest in Delta Junction, Alaska, United States (63 • 55'N, 145 • 44'W).The onset of this experiment happened in the summer of 2005 (Allison and Treseder 2008 ).Briefly, greenhouses and neighboring control plots were established in pairs in a 1 km 2 ar ea; contr ol plots were left untouched, while greenhouses (i.e.warmed treatment) warmed the soil passively during the growing season (May-September) using closed-top chambers (n = 4).The top plastic panel was r emov ed (September-May) to allow snow fall to r eac h the plots .T he air inside the greenhouses was 1.6 • C higher, on a verage , compared to control plots .T he soil temper atur e at a depth of 5 cm was 0.5 • C higher inside the greenhouses compared to control plots .T hese incr eases in temper atur e ar e within the expected r ange for high latitude ecosystems under global climate change (IPCC 2021 ).During the growing season, gutters and tubing re-directed precipitation into the greenhouses to minimize drying.Ho w ever, the w arming treatment resulted in higher evapotranspiration and reduced soil moisture by 22%, on average (i.e.warming-induced drying).In the summer of 2015, we collected four soil cores from the top 10 cm from inside center of each greenhouse and control plots (332 cm 3 ) (n = 4) and placed them inside a plastic sterile Whirl-P ak ®.Appr oximatel y one gr am of soil was immediatel y soaked in 5 ml LifeGuard TM Soil Pr eserv ation Solution (Qiagen, catalog 12 868) for RNA extraction avoiding soil disturbance as m uc h as possible, to pr e v ent tr anscription le v el c hanges .T he pr eserv ed soil solution and the soil samples were k e pt in a cooler with ice for 24 h and tr ansferr ed to a −80 • C fr eezer and 4 • C r efriger ator, r espectiv el y.The pr eserv ed soil solution and the soil samples were processed within a week of collection.
The protocol for extracting RNA and sequencing of metatranscriptomics was described in detail in Romer o-Oliv ar es and col-laborators ( 2019 ).Briefly, the Joint Genome Institute (JGI) used rRNA depletion protocols to prepare paired-end libraries, which were then fragmented and reverse transcribed.The fragmented cDN A w as treated with end-pair, A-tailing, adapter ligation, and 10 or 15 cycles of PCR and sequenced using a HiSeq 2500 system.Sequencing pr ojects ar e deposited at the JGI with project ids: 1107-496, -499, -504, -507, -509, -514, -519, and -520.Sim ultaneousl y, we carried out various isolation methods for culturing fungi from soil samples.Briefly, we prepared petri plates with malt extract agar (MEA) (20 g/L of agar, 5 g/L malt extract, 5 g/L yeast extract) and potato dextrose agar (PDA) (39 g/L of potato dextrose agar dehydrated, MP Biomedicals™) and proceed to isolate fungi by two different methods .T he first method was sprinkling 0.5 g of soil dir ectl y onto the MEA and PDA plates .T he second method was by dilution-to-extinction, where 1 g of soil was diluted in 10 mls of autoclaved water under sterile conditions and then diluted serially 5 times (1:10, 1:100, 1:1000, 1:10 000, 1:100 000).Fr om eac h dilution, we used 50 μl to inoculate in MEA and PDA plates .T his r esulted in a ppr oximatel y 60 petri plates that we incubated under two different conditions: 30 petri plates were incubated at 22 • C for 7 da ys , and 30 more petri plates were incubated at 10 • C for 3 days to discour a ge gr owth of fast growers , and then mo ved to 22 • C for 5 more da ys .We randomly selected 8 colonies from each plate (480 total colonies), inoculated them in PDA plates to obtain a clean individual colony, incubated at 22 • C for 7 da ys , and extracted DNA using the CTAB method.We amplified the ITS region using ITS1-ITS4 primers (White et al. 1990 ) and sequenced the amplicons using Sanger sequencing.We obtained good quality sequence data for 341 isolates and used BLAST (Sayers et al. 2009 ) to determine identity.We identified 10 isolates of Mortierella and 17 of Penicillium from different control and warmed plots.Once we determined we had the same species (i.e.≥99% similarity in the ITS region), we chose four isolates for our study (two from each species; one from warmed treatment and one from control conditions) and deposited sequences in NCBI GenBank ( Penicillium control, accession number: MW474735; Penicillium warmed, accession number: MW474736; Mortierella control, accession number: MW474738; Mortierella warmed, accession number: MW474737).We sent high quality DNA of these four colonies to the JGI to sequence their whole genome .T hese sequencing pr ojects ar e deposited at the JGI with pr oject ids: 1144-747, -771, -787, -789.
Metatranscriptomes and whole genomes were quality trimmed by removing adapters with Trimmomatic (v 0.39) using ILLUMINA TruSeq3-PE adapters with sliding window 4:15 and dropping reads below 25 bases long (Bolger et al. 2014 ) and quality c hec ked with FastQC (v 0.11.5)(Andr e w 2010 ).We assembled genomes using SPAdes (v 3.13.1)(Banke vic h et al. 2012 ), quality assessed with QUAST (v 4.5) (Gur e vic h et al. 2013 ), and indexed with STAR (v 2.7.5c) (Dobin et al. 2013 ).Metatranscriptomes were aligned and mapped to whole genomes using STAR (v 2.7.5c) with 'twopass-Mode Basic' due to a lack of annotated r efer ence genomes (Dobin et al. 2013 ).We used Cufflinks (v 2.2.1) with the default normalization and false discov ery r ate to estimate transcript abundance and test for differential expression (Trapnell et al. 2010 ).This pipeline resulted in multiple tables including transcript counts for control and warmed treatment samples, fold change data (i.e. the degree of change of transcript counts between control and warming in relation to the mean of normalized counts), and DNA sequences for each transcript.
We manually blasted each transcript against the GenBank database to identify them (Sayers et al. 2009 ).We selected a consensus gene based on % identity ( ≥ 80%), alignment length ( ≥ 100 bp), and E-value ( ≤ 1e −50 ), with a few exceptions (i.e.Evalues ≥ 1e −50 ) ( Table S1 ).We categorized transcripts based on InterPro (Blum et al. 2020 ) as having functions related to catabolic processes , cell homeostasis , cell morphogenesis , DNA regulation and organization, or protein biosynthesis (Table 1 ).A subset of genes in Mortierella and Penicillium could not be identified because BLAST resulted in 'hypothetical protein' or 'uncharacterized protein'.T hus , this subset of genes was left out of the analysis (listed as "unknown" in Table S1 ).We identified ATP synthase, cytoc hr ome c oxidase, heat shoc k pr oteins , histones , NADH dehydr ogenase, ribosomal pr oteins, and tr anslation elongation factor as genes of interest since they were the genes that were transcribed the most (i.e. more than 20 different transcripts each).
We used lme4 and lmerTest pac ka ge in R (Bates et al. 2015, Kuznetsova et al. 2017, R Core Team 2021 ) to carry out mixed models for each functional category, individually for specific genes of interest, and for gene expression.For each functional category, warmed treatment and species were fixed factor, plot was random factor, and transcript counts was the response variable; we used post hoc t-test to determine significant differences between species, warmed treatment, and functional category.For genes of inter est, we r an individual models for each gene of interest in each species; w armed treatment w as the fixed factor, plot w as the random factor, and transcript count was the response variable.For gene expression data of functional categories, species was fixed factor, plot was random factor, and expression fold change was the r esponse v ariable.For gene expr ession of genes of inter est, we r an individual t-tests comparing up regulated fold change expression betw een species, as w ell as do wn regulated fold c hange expr ession between species.In all cases, we used P ≤ 0.05 as significant.Our anal yses wer e non-par ametric because we r anked all data.The scripts for bioinformatics and statistical tests were deposited at https:// github.com/adrilur omer o/warming _ meta gene .Computations were performed on Pr emise, a centr al, shar ed HPC cluster at the University of New Hampshire.

Results
To answer our first question, we found that there was no significant difference between overall transcript counts of Mortierella and Penicillium between control and warmed plots ( P = 0.21), corr obor ating that these fungi were equally active under control and w armed conditions (Fig. 1 ).Ho w e v er, a br eakdown of the tr anscript counts by functional category sho w ed interspecific differences in the response of functional pathways and genes to warming.In all functional categories, except for protein biosynthesis, there was a significant interaction between species and warmed tr eatment, r e v ealing that Mortierella and Penicillium responded differ entl y to warming (catabolic processes, Fig. 2  P = 0.39; Fig. 2 c, P = 0.07; Fig. 2 e, P = 0.24, r espectiv el y).Anal yses for specific genes of interest sho w ed that the transcription for ATP synthase and cytoc hr ome c oxidase was significantly higher under warmed treatment compared to control conditions in Penicillium (Fig. 3 a, P < 0.01 and Fig. 3 b, P = 0.05, r espectiv el y), and that translation elongation factor was significantly lo w er in warmed tr eatment compar ed to contr ol conditions in Mortierella (Fig. 3 c, P = 0.05 ).
Mor eov er, our r esults show that although v ery fe w genes wer e significantly up or down regulated in response to warming ( Table S1 ), Mortierella 's fold change expression was significantly down regulated at lo w er fold change compared to Penicillium in all functional categories (catabolic processes, Fig. 2  In other w or ds, although both species had up and down regulated genes, Mortierella consistently downregulated at a lo w er fold change under control conditions compared to Penicillium , and Penicillium always upregulated at a higher fold change under control conditions compared to Mortierella .For specific genes of interest, fold c hange expr ession for all genes, except cytoc hr ome c oxidase, w as significantly do wn regulated at lo w er fold change in response to warming in Mortierella compared to Penicillium (ATP synthase, Fig. 3 h, P < 0.01; cytoc hr ome c oxidase, Fig. 3 i, P = 0.25; elongation factor, 3j, P < 0.01; heat shock protein, 3k, P < 0.01; histone, 3l, P < 0.01; NADH dehydrogenase, 3 m, P < 0.01; ribosomal protein, 3n, P < 0.01).In addition, onl y NADH dehydr ogenase and ribosomal proteins were significantly upregulated at higher fold change Table 1.Description of functional categories used to categorize transcripts, as well as examples of pr oteins involv ed in those categories.The full list of genes included in our study, their transcripts, and encoded proteins, as well as their cell function and functional category, are listed in Table S1 .

Functional Category
Genes encoding for transcripts that translate proteins for: Example, proteins involved in:

Catabolic processes
The breakdown of complex molecules to transform them into simpler forms while releasing energy.

Cell homeostasis
The maintenance of balance within a cell.
-Cha per one activity -Transport of molecules -Regulatory proteins

Cell morphogenesis
The formation of cells, specifically those involved in structural maintenance and growth.
-Cell growth -Cell structure -Cell division

DNA regulation and organization
Processes involving the organization and regulation of nucleic acids in the cell.
-DNA replication -DNA pac ka ging -Transcription factors

Protein biosynthesis
The production of proteins.
-Ribosomal proteins Asterisks denote significance at P ≤ 0.05 between control and warmed samples within each species (a-e) and significance between fold change expression between species (f-j).
In terms of str ategizing r esource inv estment under warming, Mortierella and Penicillium again displayed significant differences (Fig. 4 ).In response to warming, Mortierella transcribed mostly genes involved in glutamate metabolism (1-pyrroline-5-carboxylate dehydrogenase) and methylation control (adenosylhomocysteinase).P enicillium tr anscribed man y genes, including those involved in biosynthesis of pyrimidine (aspartate carbamoyltr ansfer ase), citric acid metabolism (citrate synthase), biosynthesis of glutamine (glutamine synthase), breakdown of sugars (glycoside hydrolase and transketolase), secondary metabolites (ter penoid synthase), br eakdown of xylose (xylose r e-ductase), and metabolism of sulfur (sulfite reductase) ( Table S1 ).Some genes wer e tr anscribed by both fungal species but differed in their warming response.For example, both fungi transcribed genes involved in urea production and glycolysis, but Penicillium transcribed more under warming in contrast to Mortierella, whic h tr anscribed less.As suc h, fold c hange expr ession for these genes a ppear ed as upr egulated for P enicillium and down r egulated for Mortierella ( Table S1 ) (Fig. 4 ).Mor eov er, in r esponse to warming, P enicillium tr anscribed genes involved in cell wall formation, suc h as 1,3-beta-glucanosyltr ansfer ase and α-glucan synthase, as well as membr ane pr oteins, actin, and tubulin.Mortierella also transcribed genes for actin and tubulin but in lo w er abundance ( Table S1 ).

Discussion
Protein biosynthesis genes were the most abundant transcripts in Penicillium and Mortierella in both control conditions and warmed treatment (Fig. 2 and Table S1 ).Most protein biosynthesis transcripts in our data are involved in ribosome biogenesis (e.g.40S and 60S ribosomal proteins).The production of ribosomes is an energy demanding process associated with rapid growth, but can also be associated with o xidati v e str ess pr otection (Albert et al. 2019 ).Under control conditions, Mortierella and Penicillium may be transcribing ribosomal proteins for rapid growth, while under warmed conditions ribosomal proteins may be conferring protection to o xidati v e str ess.Since Mortierella and Penicillium maintained and incr eased, r espectiv el y, their inv estment in catabolic processes under warming (Fig. 2 a), reacti ve o xygen-a by-product of aerobic metabolism-may be accumulating in cells, causing o xidati v e str ess (Shimizu 2018 ).Ther efor e, under warming, Mortierella and Penicillium may need to k ee p up with the production of ribosomes for protection against o xidati ve stress .T his strategy may be especially needed for Mortierella, since antioxidant-related genes were transcribed at lo w er abundance under warming and drying (e.g.thioredoxin) ( Table S1 ).Inter estingl y, ribosome biogenesis has been positiv el y corr elated with the ability of certain fungi to r a pidl y consume glucose through the fermentation pathway (Mullis et al. 2020 ).This relationship could allow them to k ee p gr owing thr ough the consumption of sugars via lo w-efficienc y fermentation (Mullis et al. 2020 ).Indeed, the ability to ferment, especiall y under aer obic conditions (i.e.Cr abtr ee effect) has been associated with a selective adv anta ge in yeast (Piškur et al. 2006 ).But the ability to ferment under aerobic conditions has also been documented in other fungi (e.g.Mullis et al. 2020 ).In our study, genes that may be related to the process of fermentation, such as zinc-dependent alcohol dehydrogenase (Raj et al. 2014 ), were transcribed at higher abundance under warming in Penicillium ( Table S1 ).Although alcohol dehydrogenases have other functions that do not necessaril y r elate to fermentation, these r esults suggest that Penicillium could be fermenting to acquire energy under warming.If so, this strategy might be pr oviding P enicillium with a competiti ve ad vantage over other fungi in response to the warming treatment.
Only two specific genes of interest, ATP synthase and cytoc hr ome c oxidase, were transcribed more under warming compared to control conditions, and only in the case of Penicillium (Fig. 3 ).Even though the transcription of heat shock proteins, as a whole, was not significantly different between control conditions and warmed treatment (Fig. 3 d), the transcription of heat shock protein 70 and 90, which are known to have a role in morphogenesis , heat stress , and pH stress (Tiwari et al. 2015 ) was highly upregulated in response to warming in both fungal species ( Table S1 ).These results suggest that under warming, Mortierella and Penicillium may be investing in the production of pr otectiv e molecules since they may have been experiencing heat stress and/or pH str ess.Similar r esults hav e been reported in other fungi exposed to heat stress and/or pH str ess.Specificall y, Sc hizophyllum commune transcribed heat shock protein 70 and 90 after experiencing a shift in temper atur e fr om 21 • C to 55 • C (Higgins and Lilly 1993 ).Also, Neurospor a cr assa and Aspergillus nidulans transcribed genes for heat shock protein 70 and 90 in response to heat shock and extr acellular pH c hanges (Mohsenzadeh et al. 1998, Squina et al. 2010, Fr eitas et al. 2011 ).Ev en though Mortierella and P enicillium experienced a r elativ el y small temper atur e shift ( ∼0.5 • C-1.5 • C on av er a ge), these c hanges in abiotic conditions over a long period of time ( ∼10 years) may have been exerting chronic stress, resulting in the upregulation of certain heat shoc k pr otein genes in response to warming ( Table S1 ).Although these proteins are known to be produced as a response to unfavorable conditions, biotic or abiotic, they also have a role in basic biological processes, such as gene transcription and protein translation (Tiwari et al. 2015 ).Aside fr om c hanges in gene expr ession, fungi may shift the function of heat shock proteins and use them for transcription and translation under control conditions, and for cell homeostasis and protection under w arming.Accor dingly, this shift in function would not change the number of transcripts between control and warmed samples.It has been proposed that the upregulation of specific genes plays a critical role in the retention of said genes (Zhang et al. 2019 ).T hus , further attention to upregulation of genes in wild fungal communities exposed to global change drivers may provide insight into adaptation strategies and traits that may be under selection.
We speculate that increases in transcription of most functional categories in Penicillium but not Mortierella (Fig. 2 and Table S1 ) could support the idea that e v en though both species wer e activ e under warming, Penicillium seemed to be thriving while Mortierella seemed to be surviving (Fig. 4 ).Specificall y, P enicillium sho w ed increased activity in most metabolic processes, except protein biosynthesis which remained unchanged (Fig. 2 ).In addition, we found evidence that that Penicillium may have been actively growing because it transcribed genes involved in cell wall and membr ane formation.Contr astingl y, Mortierella sho w ed reduced activity in cell homeostasis and DNA regulation and organization, and no change in catabolic processes, cell morphogenesis, and protein biosynthesis which may indicate that Mortierella was investing in cell structure maintenance rather than growth.Altogether, this suggests that responses to warming, and thus, potential adaptation pathwa ys , ma y be species-specific.Ho w e v er, both species either maintained or incr eased inv estment in catabolic processes, cell morphogenesis, and protein biosynthesis, suggesting that prioritizing those processes may be critical for their survival.But the fact that the total transcription activity of neither fungi differed between control conditions and warmed treatment suggests that the interspecific differences in functional gene transcription did not result in a change in total activity levels of the fungi (Fig. 1 ) and that both fungi have been able to survive a decade of chronic stress.
By studying two fungal species and their response to warming, we present a model study to tr ac k species-le v el r esponses to global change drivers in a natural soil environment.Our results r epr esent a sna pshot specific to the day and time when we collected soil.T hus , futur e studies should concentr ate efforts on c hanges acr oss time (i.e .minutes , da ys , months , years) as r esearc h has shown that microbial resource investment is highly dynamic and varies with season (Žif čáková et al. 2016 , 2017 ).Considering micr o-scale v ariations should also be a priority, as we found substantial plot variation ( Fig. S1 ) which was probably the effect of plot-specific differences in soil conditions and/or plot microclimate.Even though these variations probably do not have an effect at the ecosystem scale in our work, the added effect of microscale inter actions may giv e rise to lar ge-scale effects on biogeoc hemical cycles (Kim andOr 2019 , König et al. 2020 ).Mor eov er, futur e studies should explore more than two fungal species to provide a broader overview of the metabolic investment and potential ada ptation str ateg ies that fung i ar e under going when exposed to warming.Specificall y, inv estigating how transcription changes in fungi that increase and decrease in abundance under warming ma y pro vide a good understanding of whic h genes pr ovide a competiti ve ad vantage/disad vantage under stress .Similarly, in vestigating fungi with different ecological functions and focusing on functional genes, such as decomposition related genes (e .g. C AZy) (Lombard et al. 2014 ), provides an ov ervie w on ho w w arming is affecting the fungal community more broadly, as well as the carbon cycling processes they mediate.Although we identified some CAZy transcripts in our dataset, these were not significantly different between the control conditions and warming treatment ( Table S1 ).Finall y, futur e studies will benefit from increased computational po w er in high-performance computer clusters and the de v elopment of memory-efficient software, as access to random access memory (i.e.RAM) limited the amount of samples that we could analyze (Romero-Olivares et al. 2019 ).
In conclusion, our work offers insight into ho w tw o fungal species ar e r esponding to warming in a natural soil environment.We present a model study, which can be replicated in other ecosystems, to tr ac k species-le v el r esponses in a natur al soil environment and provide insight into the specific strategies that local fungal species undergo to ensure their survival under global climate change.We found evidence that investing in the transcription of critical genes involved in catabolic processes, cell mor phogenesis, and pr otein biosynthesis under warming has allo w ed Mortierella and Penicillium to withstand over a decade of c hr onic str ess .T his suggests that in vesting in maintaining catabolic rates and processes while growing and protecting their cells may be a good strategy for fungi to survive under global climate change.

Figure 1 .
Figure 1.Total transcript counts in Mortierella and Penicillium in control and warmed samples.Box and whisker plots show the distribution of the data with lo w er and upper quartiles, mean, and lo w est and highest observations plotted (n = 4).Each point represents the transcript count of a specific gene.Total transcript counts were not significantly different between control and warmed samples ( P = 0.21).

Figure 2 .
Figure 2. Transcript counts in Mortierella and Penicillium in control and warmed samples (a-e) and fold change expression in response to warming (f-j) by functional category.Box and whisker plots show the distribution of the data with lower and upper quartiles, mean, and lowest and highest observations plotted (n = 4).Each point represents the transcript count of a specific gene (a-e) and the fold change expression of a specific gene (f-j).Asterisks denote significance at P ≤ 0.05 between control and warmed samples within each species (a-e) and significance between fold change expression between species (f-j).

Figure 3 .
Figure 3. Transcript counts in Mortierella and Penicillium in control and warmed samples (a-g) and fold change expression in response to warming (h-n) in response to warming by genes of interest.Box and whisker plots show the distribution of the data with lo w er and upper quartiles, mean, and lo w est and highest observations plotted (n = 4).Each point r epr esents the transcript count of a specific gene (a-g) and the fold change expression of a specific gene (h-n).Asterisks denote significance at P ≤ 0.05 between control and warmed samples within each species (a-g) and significance between fold c hange expr ession between species (h-n).

Figure 4 .
Figure 4. Summary of responses of Mortierella and Penicillium under warming.Mortierella downregulates at a lower fold change under warming, while P enicillium upr egulates at a higher fold c hange under w arming.Secondary metabolites, biosynthesis of p yrimidine, citric acid metabolism, biosynthesis of glutamine, breakdown of sugars, and metabolism of sulfur are a few examples of unique gene transcripts in Penicillium .Methylation control and glutamate metabolism are a few examples of unique gene transcripts in Mortierella .Contrastingly, production of urea, formation of cell wall, and gl ycol ysis wer e gene tr anscripts pr esent in both Mortierella and P enicillium .Illustr ation cr eated with BioRender.com,license a gr eement UG24RGWD3U.